Businesses must process large amounts of data to make decisions and be successful. The data is often provided in formats such as reports. To build a meaningful report, businesses are relying on multi-tenanted SAAS analytic companies. Building and providing meaningful analytics typically require a large amount of resources and have a high cost.
Building the reports typically requires acquiring data, transforming the data to a meaningful format, and performing analytics of the meaningful data to generate the report. Data storage, transformation and manipulation require data schemas to store the data, transform the data and process the data. These tasks are typically performed manually by administrators. For example, as a data format changes, an administrator must manually change data schema in one or more places as well as manually have code generated for processing the new data format. The manual work requires quality assurance resources, and is time consuming. When each of a plurality of tenants wishes to change schemas for one or more applications, it can be costly and time consuming to keep up with the changes in data mapping. There is a need for a more efficient data mapping for businesses.